Optimizing just-in-time compiling for a java application executing on a compute node

ABSTRACT

Methods, systems, and products are disclosed for optimizing just-in-time (‘JIT’) compiling for a Java application executing on a compute node, the compute node having installed upon it a Java Virtual Machine (‘JVM’) capable of supporting the Java application, that include: identifying, by an application manager, a particular portion of the Java application; assigning, by the application manager, a JIT level to the particular portion of the Java application; and jitting, by the JVM installed on the compute node, the particular portion of the Java application in dependence upon the JIT level assigned to that particular portion of the Java application.

CROSS-REFERENCE TO RELATED APPLICATION

This application is a continuation application of and claims priorityfrom U.S. patent application Ser. No. 12/109,271, filed on Apr. 24,2008.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The field of the invention is data processing, or, more specifically,methods, apparatus, and products for optimizing just-in-time (‘JIT’)compiling for a Java application executing on a compute node.

2. Description of Related Art

The development of the EDVAC computer system of 1948 is often cited asthe beginning of the computer era. Since that time, computer systemshave evolved into extremely complicated devices. Today's computers aremuch more sophisticated than early systems such as the EDVAC. Computersystems typically include a combination of hardware and softwarecomponents, application programs, operating systems, processors, buses,memory, input/output devices, and so on. As advances in semiconductorprocessing and computer architecture push the performance of thecomputer higher and higher, more sophisticated computer software hasevolved to take advantage of the higher performance of the hardware,resulting in computer systems today that are much more powerful thanjust a few years ago.

Parallel computing is an area of computer technology that hasexperienced advances. Parallel computing is the simultaneous executionof the same task (split up and specially adapted) on multiple processorsin order to obtain results faster. Parallel computing is based on thefact that the process of solving a problem usually can be divided intosmaller tasks, which may be carried out simultaneously with somecoordination.

Parallel computers execute parallel algorithms. A parallel algorithm canbe split up to be executed a piece at a time on many differentprocessing devices, and then put back together again at the end to get adata processing result. Some algorithms are easy to divide up intopieces. Splitting up the job of checking all of the numbers from one toa hundred thousand to see which are primes could be done, for example,by assigning a subset of the numbers to each available processor, andthen putting the list of positive results back together. In thisspecification, the multiple processing devices that execute theindividual pieces of a parallel program are referred to as ‘computenodes.’ A parallel computer is composed of compute nodes and otherprocessing nodes as well, including, for example, input/output (‘I/O’)nodes, and service nodes.

Parallel algorithms are valuable because it is faster to perform somekinds of large computing tasks via a parallel algorithm than it is via aserial (non-parallel) algorithm, because of the way modern processorswork. It is far more difficult to construct a computer with a singlefast processor than one with many slow processors with the samethroughput. There are also certain theoretical limits to the potentialspeed of serial processors. On the other hand, every parallel algorithmhas a serial part and so parallel algorithms have a saturation point.After that point adding more processors does not yield any morethroughput but only increases the overhead and cost.

Parallel algorithms are designed also to optimize one more resource thedata communications requirements among the nodes of a parallel computer.There are two ways parallel processors communicate, shared memory ormessage passing. Shared memory processing needs additional locking forthe data and imposes the overhead of additional processor and bus cyclesand also serializes some portion of the algorithm.

Message passing processing uses high-speed data communications networksand message buffers, but this communication adds transfer overhead onthe data communications networks as well as additional memory need formessage buffers and latency in the data communications among nodes.Designs of parallel computers use specially designed data communicationslinks so that the communication overhead will be small but it is theparallel algorithm that decides the volume of the traffic.

Many data communications network architectures are used for messagepassing among nodes in parallel computers. Compute nodes may beorganized in a network as a ‘torus’ or ‘mesh,’ for example. Also,compute nodes may be organized in a network as a tree. A torus networkconnects the nodes in a three-dimensional mesh with wrap around links.Every node is connected to its six neighbors through this torus network,and each node is addressed by its x,y,z coordinate in the mesh. A torusnetwork lends itself to point to point operations. In a tree network,the nodes typically are connected into a binary tree: each node has aparent, and two children (although some nodes may only have zerochildren or one child, depending on the hardware configuration). Incomputers that use a torus and a tree network, the two networkstypically are implemented independently of one another, with separaterouting circuits, separate physical links, and separate message buffers.A tree network provides high bandwidth and low latency for certaincollective operations, message passing operations where all computenodes participate simultaneously, such as, for example, an allgather.

The parallel applications that execute on the nodes in the datacommunications networks may be implemented in a variety of softwareprogramming languages, including the various versions and derivatives ofJava™ technology promulgated by Sun Microsystems. Java applicationsgenerally run in a virtual execution environment called the Java VirtualMachine (‘JVM’), rather than running directly on the computer hardware.The Java application is typically compiled into byte-code form, and thencompiled in a just-in-time (‘JIT’) manner, or on-the-fly, by the JVMinto JIT code representing hardware commands specific to the hardwareplatform on which the JVM is installed.

SUMMARY OF THE INVENTION

Methods, systems, and products are disclosed for optimizing just-in-time(‘JIT’) compiling for a Java application executing on a compute node,the compute node having installed upon it a Java Virtual Machine (‘JVM’)capable of supporting the Java application, that include: identifying,by an application manager, a particular portion of the Java application;assigning, by the application manager, a JIT level to the particularportion of the Java application; and jitting, by the JVM installed onthe compute node, the particular portion of the Java application independence upon the JIT level assigned to that particular portion of theJava application.

The foregoing and other objects, features and advantages of theinvention will be apparent from the following more particulardescriptions of exemplary embodiments of the invention as illustrated inthe accompanying drawings wherein like reference numbers generallyrepresent like parts of exemplary embodiments of the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an exemplary system for optimizing JIT compiling fora Java application executing on a compute node according to embodimentsof the present invention.

FIG. 2 sets forth a block diagram of an exemplary compute node useful ina parallel computer capable of optimizing JIT compiling for a Javaapplication executing on a compute node according to embodiments of thepresent invention.

FIG. 3A illustrates an exemplary Point To Point Adapter useful insystems capable of optimizing JIT compiling for a Java applicationexecuting on a compute node according to embodiments of the presentinvention.

FIG. 3B illustrates an exemplary Global Combining Network Adapter usefulin systems capable of optimizing JIT compiling for a Java applicationexecuting on a compute node according to embodiments of the presentinvention.

FIG. 4 sets forth a line drawing illustrating an exemplary datacommunications network optimized for point to point operations useful insystems capable of optimizing JIT compiling for a Java applicationexecuting on a compute node in accordance with embodiments of thepresent invention.

FIG. 5 sets forth a line drawing illustrating an exemplary datacommunications network optimized for collective operations useful insystems capable of optimizing JIT compiling for a Java applicationexecuting on a compute node in accordance with embodiments of thepresent invention.

FIG. 6 sets forth a block diagram illustrating an exemplary systemuseful in optimizing JIT compiling for a Java application executing on acompute node according to embodiments of the present invention.

FIG. 7 sets forth a flow chart illustrating an exemplary method foroptimizing JIT compiling for a Java application executing on a computenode according to embodiments of the present invention.

DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS

Exemplary methods, apparatus, and computer program products foroptimizing JIT compiling for a Java application executing on a computenode according to embodiments of the present invention are describedwith reference to the accompanying drawings, beginning with FIG. 1. FIG.1 illustrates an exemplary system for optimizing JIT compiling for aJava application executing on a compute node according to embodiments ofthe present invention. The system of FIG. 1 includes a parallel computer(100), non-volatile memory for the computer in the form of data storagedevice (118), an output device for the computer in the form of printer(120), and an input/output device for the computer in the form ofcomputer terminal (122). Parallel computer (100) in the example of FIG.1 includes a plurality of compute nodes (102).

The compute nodes (102) are coupled for data communications by severalindependent data communications networks including a Joint Test ActionGroup (‘JTAG’) network (104), a global combining network (106) which isoptimized for collective operations, and a torus network (108) which isoptimized point to point operations. The global combining network (106)is a data communications network that includes data communications linksconnected to the compute nodes so as to organize the compute nodes as atree. Each data communications network is implemented with datacommunications links among the compute nodes (102). The datacommunications links provide data communications for parallel operationsamong the compute nodes of the parallel computer. The links betweencompute nodes are bi-directional links that are typically implementedusing two separate directional data communications paths.

In addition, the compute nodes (102) of parallel computer are organizedinto at least one operational group (132) of compute nodes forcollective parallel operations on parallel computer (100). Anoperational group of compute nodes is the set of compute nodes uponwhich a collective parallel operation executes. Collective operationsare implemented with data communications among the compute nodes of anoperational group. Collective operations are those functions thatinvolve all the compute nodes of an operational group. A collectiveoperation is an operation, a message-passing computer programinstruction that is executed simultaneously, that is, at approximatelythe same time, by all the compute nodes in an operational group ofcompute nodes. Such an operational group may include all the computenodes in a parallel computer (100) or a subset all the compute nodes.Collective operations are often built around point to point operations.A collective operation requires that all processes on all compute nodeswithin an operational group call the same collective operation withmatching arguments. A ‘broadcast’ is an example of a collectiveoperation for moving data among compute nodes of an operational group. A‘reduce’ operation is an example of a collective operation that executesarithmetic or logical functions on data distributed among the computenodes of an operational group. An operational group may be implementedas, for example, an MPI ‘communicator.’

‘MPI’ refers to ‘Message Passing Interface,’ a prior art parallelcommunications library, a module of computer program instructions fordata communications on parallel computers. Examples of prior-artparallel communications libraries that may be improved for use withsystems according to embodiments of the present invention include MPIand the ‘Parallel Virtual Machine’ (‘PVM’) library. PVM was developed bythe University of Tennessee, The Oak Ridge National Laboratory, andEmory University. MPI is promulgated by the MPI Forum, an open groupwith representatives from many organizations that define and maintainthe MPI standard. MPI at the time of this writing is a de facto standardfor communication among compute nodes running a parallel program on adistributed memory parallel computer. This specification sometimes usesMPI terminology for ease of explanation, although the use of MPI as suchis not a requirement or limitation of the present invention.

Some collective operations have a single originating or receivingprocess running on a particular compute node in an operational group.For example, in a ‘broadcast’ collective operation, the process on thecompute node that distributes the data to all the other compute nodes isan originating process. In a ‘gather’ operation, for example, theprocess on the compute node that received all the data from the othercompute nodes is a receiving process. The compute node on which such anoriginating or receiving process runs is referred to as a logical root.

Most collective operations are variations or combinations of four basicoperations: broadcast, gather, scatter, and reduce. The interfaces forthese collective operations are defined in the MPI standards promulgatedby the MPI Forum. Algorithms for executing collective operations,however, are not defined in the MPI standards. In a broadcast operation,all processes specify the same root process, whose buffer contents willbe sent. Processes other than the root specify receive buffers. Afterthe operation, all buffers contain the message from the root process.

In a scatter operation, the logical root divides data on the root intosegments and distributes a different segment to each compute node in theoperational group. In scatter operation, all processes typically specifythe same receive count. The send arguments are only significant to theroot process, whose buffer actually contains sendcount*N elements of agiven data type, where N is the number of processes in the given groupof compute nodes. The send buffer is divided and dispersed to allprocesses (including the process on the logical root). Each compute nodeis assigned a sequential identifier termed a ‘rank.’ After theoperation, the root has sent sendcount data elements to each process inincreasing rank order. Rank 0 receives the first sendcount data elementsfrom the send buffer. Rank 1 receives the second sendcount data elementsfrom the send buffer, and so on.

A gather operation is a many-to-one collective operation that is acomplete reverse of the description of the scatter operation. That is, agather is a many-to-one collective operation in which elements of adatatype are gathered from the ranked compute nodes into a receivebuffer in a root node.

A reduce operation is also a many-to-one collective operation thatincludes an arithmetic or logical function performed on two dataelements. All processes specify the same ‘count’ and the same arithmeticor logical function. After the reduction, all processes have sent countdata elements from computer node send buffers to the root process. In areduction operation, data elements from corresponding send bufferlocations are combined pair-wise by arithmetic or logical operations toyield a single corresponding element in the root process's receivebuffer. Application specific reduction operations can be defined atruntime. Parallel communications libraries may support predefinedoperations. MPI, for example, provides the following pre-definedreduction operations:

MPI_MAX maximum MPI_MIN minimum MPI_SUM sum MPI_PROD product MPI_LANDlogical and MPI_BAND bitwise and MPI_LOR logical or MPI_BOR bitwise orMPI_LXOR logical exclusive or MPI_BXOR bitwise exclusive or

In addition to compute nodes, the parallel computer (100) includesinput/output (‘I/O’) nodes (110, 114) coupled to compute nodes (102)through the global combining network (106). The compute nodes in theparallel computer (100) are partitioned into processing sets such thateach compute node in a processing set is connected for datacommunications to the same I/O node. Each processing set, therefore, iscomposed of one I/O node and a subset of compute nodes (102). The ratiobetween the number of compute nodes to the number of I/O nodes in theentire system typically depends on the hardware configuration for theparallel computer. For example, in some configurations, each processingset may be composed of eight compute nodes and one I/O node. In someother configurations, each processing set may be composed of sixty-fourcompute nodes and one I/O node. Such example are for explanation only,however, and not for limitation. Each I/O nodes provide I/O servicesbetween compute nodes (102) of its processing set and a set of I/Odevices. In the example of FIG. 1, the I/O nodes (110, 114) areconnected for data communications I/O devices (118, 120, 122) throughlocal area network (‘LAN’) (130) implemented using high-speed Ethernet.

The parallel computer (100) of FIG. 1 also includes a service node (116)coupled to the compute nodes through one of the networks (104). Servicenode (116) provides services common to pluralities of compute nodes,administering the configuration of compute nodes, loading programs intothe compute nodes, starting program execution on the compute nodes,retrieving results of program operations on the computer nodes, and soon. Service node (116) runs a service application (124) and communicateswith users (128) through a service application interface (126) that runson computer terminal (122).

In the example of FIG. 1, the service node (116) has installed upon itan application manager (125). The application manager (125) of FIG. 1includes a set of computer program instructions capable of optimizingJIT compiling for a Java application executing on a compute nodeaccording to embodiments of the present invention. The applicationmanager (125) operates generally for optimizing JIT compiling for a Javaapplication executing on a compute node according to embodiments of thepresent invention by: identifying particular portion of the Javaapplication and assigning a JIT level to the particular portion of theJava application. Although FIG. 1 illustrates the application manager(125) installed on a service node, readers will note that such anexample is for explanation only and not for limitation. An applicationmanager is a software component that may be installed on any computenodes or other computer as will occur to those of skill in the art.

Each compute node (102) of FIG. 1 has installed upon it a Java VirtualMachine (‘JVM’) (200) capable of supporting a Java application. Each JVM(200) of FIG. 1 includes a set of computer program instructions capableof optimizing JIT compiling for a Java application executing on acompute node according to embodiments of the present invention. Each JVM(200) operates generally for optimizing JIT compiling for a Javaapplication executing on a compute node according to embodiments of thepresent invention by jitting a particular portion of a Java applicationin dependence upon the JIT level assigned to that particular portion ofthe Java application. The term ‘jitting’ refers to the process oftranslating byte code into native platform machine code executable onthe platform's processor and optimizing the machine code for enhancedexecution performance.

A JIT level, also referred to as a ‘JIT mode,’ specifies the type of JITcompiling and optimizations performed on a particular portion of a Javaapplication. The number and type of JIT levels available for a JVM varyfrom one implementation to another. For one example, Sun Microsystems'JVM has two major JIT levels—client and server. In the client JIT level,minimal compilation and optimization is performed in an effort to reducethe startup time required for the application to begin executing. In theserver JIT level, initial startup time is sacrificed, and extensivecompilation and optimization is performed to maximize applicationperformance when the application executes. Readers will note that thesetwo JIT level are for example and explanation only and not forlimitations. Other JIT levels and other terms besides ‘client’ and‘server’ may be used to identify JIT level as will occur to those ofskill in the art.

In the example of FIG. 1, the plurality of compute nodes (102) areimplemented in a parallel computer (100) and are connected togetherusing a plurality of data communications networks (104, 106, 108). Thepoint to point network (108) is optimized for point to point operations.The global combining network (106) is optimized for collectiveoperations. Although optimizing JIT compiling for a Java applicationexecuting on a compute node according to embodiments of the presentinvention is described above in terms of optimizing JIT compiling for aJava application executing on a parallel computer, readers will notethat such an embodiment is for explanation only and not for limitation.In fact, optimizing JIT compiling for a Java application executing on acompute node according to embodiments of the present invention may beimplemented using a variety of computer systems composed of a pluralityof nodes network-connected together, including for example a cluster ofnodes, a distributed computing system, a grid computing system, and soon.

The arrangement of nodes, networks, and I/O devices making up theexemplary system illustrated in FIG. 1 are for explanation only, not forlimitation of the present invention. Data processing systems capable ofoptimizing JIT compiling for a Java application executing on a computenode according to embodiments of the present invention may includeadditional nodes, networks, devices, and architectures, not shown inFIG. 1, as will occur to those of skill in the art. Although theparallel computer (100) in the example of FIG. 1 includes sixteencompute nodes (102), readers will note that parallel computers capableof optimizing JIT compiling for a Java application executing on acompute node according to embodiments of the present invention mayinclude any number of compute nodes. In addition to Ethernet and JTAG,networks in such data processing systems may support many datacommunications protocols including for example TCP (Transmission ControlProtocol), IP (Internet Protocol), and others as will occur to those ofskill in the art. Various embodiments of the present invention may beimplemented on a variety of hardware platforms in addition to thoseillustrated in FIG. 1.

Optimizing JIT compiling for a Java application executing on a computenode according to embodiments of the present invention may be generallyimplemented on a parallel computer that includes a plurality of computenodes, among other types of exemplary systems. In fact, such computersmay include thousands of such compute nodes. Each compute node is inturn itself a kind of computer composed of one or more computerprocessors, its own computer memory, and its own input/output adapters.For further explanation, therefore, FIG. 2 sets forth a block diagram ofan exemplary compute node (152) useful in a parallel computer capable ofoptimizing JIT compiling for a Java application executing on a computenode according to embodiments of the present invention.

The compute node (152) of FIG. 2 includes one or more computerprocessors (164) as well as random access memory (‘RAM’) (156). Theprocessors (164) are connected to RAM (156) through a high-speed memorybus (154) and through a bus adapter (194) and an extension bus (168) toother components of the compute node (152). Stored in RAM (156) is aJava application (158), a module of computer program instructions thatcarries out parallel, user-level data processing using one or more Javaclasses.

Also stored in RAM (156) is an application manager (125). Theapplication manager (125) of FIG. 2 includes a set of computer programinstructions capable of optimizing JIT compiling for a Java applicationexecuting on a compute node according to embodiments of the presentinvention. The application manager (125) operates generally foroptimizing JIT compiling for a Java application executing on a computenode according to embodiments of the present invention by: identifyingparticular portion of the Java application (158) and assigning a JITlevel to the particular portion of the Java application (158).

Also stored in RAM (156) is a Java Virtual Machine (‘JVM’) (200). TheJVM (200) of FIG. 2 is a set of computer software programs and datastructures which implements a virtual execution environment for aspecific hardware platform. The JVM (200) of FIG. 2 accepts the Javaapplication (158) for execution in a computer intermediate language,commonly referred to as Java byte code, which is a hardware-independentcompiled form of the Java application (158). In such a manner, the JVM(200) of FIG. 2 serves to abstract the compiled version of the Javaapplication (158) from the hardware of node (152) because the JVM (200)handles the hardware specific implementation details of executing theapplication (158) during runtime. Abstracting the hardware details of aplatform from the compiled form of a Java application allows theapplication to be compiled once into byte code, yet run on a variety ofhardware platforms.

The JVM (200) of FIG. 2 is improved for optimizing JIT compiling for aJava application executing on a compute node according to embodiments ofthe present invention. The JVM (200) of FIG. 2 operates generally foroptimizing JIT compiling for a Java application executing on a computenode according to embodiments of the present invention by: jitting aparticular portion of a Java application in dependence upon the JITlevel assigned to that particular portion of the Java application (158).

Also stored RAM (156) is a messaging module (161), a library of computerprogram instructions that carry out parallel communications amongcompute nodes, including point to point operations as well as collectiveoperations. The Java application (158) effects data communications withother applications running on other compute nodes by calling softwareroutines in the messaging modules (161). A library of parallelcommunications routines may be developed from scratch for use in systemsaccording to embodiments of the present invention, using a traditionalprogramming language such as the C programming language, and usingtraditional programming methods to write parallel communicationsroutines. Alternatively, existing prior art libraries may be used suchas, for example, the ‘Message Passing Interface’ (‘MPI’) library, the‘Parallel Virtual Machine’ (‘PVM’) library, and the Aggregate RemoteMemory Copy Interface (‘ARMCI’) library.

Also stored in RAM (156) is an operating system (162), a module ofcomputer program instructions and routines for an application program'saccess to other resources of the compute node. It is typical for anapplication program and parallel communications library in a computenode of a parallel computer to run a single thread of execution with nouser login and no security issues because the thread is entitled tocomplete access to all resources of the node. The quantity andcomplexity of tasks to be performed by an operating system on a computenode in a parallel computer therefore are smaller and less complex thanthose of an operating system on a serial computer with many threadsrunning simultaneously. In addition, there is no video I/O on thecompute node (152) of FIG. 2, another factor that decreases the demandson the operating system. The operating system may therefore be quitelightweight by comparison with operating systems of general purposecomputers, a pared down version as it were, or an operating systemdeveloped specifically for operations on a particular parallel computer.Operating systems that may usefully be improved, simplified, for use ina compute node include UNIX™, Linux™, Microsoft Vista™, AIX™, IBM'si5/OS™, and others as will occur to those of skill in the art.

The exemplary compute node (152) of FIG. 2 includes severalcommunications adapters (172, 176, 180, 188) for implementing datacommunications with other nodes of a parallel computer. Such datacommunications may be carried out serially through RS-232 connections,through external buses such as USB, through data communications networkssuch as IP networks, and in other ways as will occur to those of skillin the art. Communications adapters implement the hardware level of datacommunications through which one computer sends data communications toanother computer, directly or through a network. Examples ofcommunications adapters useful in systems for optimizing JIT compilingfor a Java application executing on a compute node according toembodiments of the present invention include modems for wiredcommunications, Ethernet (IEEE 802.3) adapters for wired networkcommunications, and 802.11b adapters for wireless networkcommunications.

The data communications adapters in the example of FIG. 2 include aGigabit Ethernet adapter (172) that couples example compute node (152)for data communications to a Gigabit Ethernet (174). Gigabit Ethernet isa network transmission standard, defined in the IEEE 802.3 standard,that provides a data rate of 1 billion bits per second (one gigabit).Gigabit Ethernet is a variant of Ethernet that operates over multimodefiber optic cable, single mode fiber optic cable, or unshielded twistedpair.

The data communications adapters in the example of FIG. 2 includes aJTAG Slave circuit (176) that couples example compute node (152) fordata communications to a JTAG Master circuit (178). JTAG is the usualname used for the IEEE 1149.1 standard entitled Standard Test AccessPort and Boundary-Scan Architecture for test access ports used fortesting printed circuit boards using boundary scan. JTAG is so widelyadapted that, at this time, boundary scan is more or less synonymouswith JTAG. JTAG is used not only for printed circuit boards, but alsofor conducting boundary scans of integrated circuits, and is also usefulas a mechanism for debugging embedded systems, providing a convenient“back door” into the system. The example compute node of FIG. 2 may beall three of these: It typically includes one or more integratedcircuits installed on a printed circuit board and may be implemented asan embedded system having its own processor, its own memory, and its ownI/O capability. JTAG boundary scans through JTAG Slave (176) mayefficiently configure processor registers and memory in compute node(152) for use in optimizing JIT compiling for a Java applicationexecuting on a compute node according to embodiments of the presentinvention.

The data communications adapters in the example of FIG. 2 includes aPoint To Point Adapter (180) that couples example compute node (152) fordata communications to a network (108) that is optimal for point topoint message passing operations such as, for example, a networkconfigured as a three-dimensional torus or mesh. Point To Point Adapter(180) provides data communications in six directions on threecommunications axes, x, y, and z, through six bidirectional links: +x(181), −x (182), +y (183), −y (184), +z (185), and −z (186).

The data communications adapters in the example of FIG. 2 includes aGlobal Combining Network Adapter (188) that couples example compute node(152) for data communications to a network (106) that is optimal forcollective message passing operations on a global combining networkconfigured, for example, as a binary tree. The Global Combining NetworkAdapter (188) provides data communications through three bidirectionallinks: two to children nodes (190) and one to a parent node (192).

Example compute node (152) includes two arithmetic logic units (‘ALUs’).ALU (166) is a component of processor (164), and a separate ALU (170) isdedicated to the exclusive use of Global Combining Network Adapter (188)for use in performing the arithmetic and logical functions of reductionoperations. Computer program instructions of a reduction routine inparallel communications library (160) may latch an instruction for anarithmetic or logical function into instruction register (169). When thearithmetic or logical function of a reduction operation is a ‘sum’ or a‘logical or,’ for example, Global Combining Network Adapter (188) mayexecute the arithmetic or logical operation by use of ALU (166) inprocessor (164) or, typically much faster, by use dedicated ALU (170).

The example compute node (152) of FIG. 2 includes a direct memory access(‘DMA’) controller (195), which is computer hardware for direct memoryaccess and a DMA engine (195), which is computer software for directmemory access. Direct memory access includes reading and writing tomemory of compute nodes with reduced operational burden on the centralprocessing units (164). A DMA transfer essentially copies a block ofmemory from one compute node to another. While the CPU may initiates theDMA transfer, the CPU does not execute it. In the example of FIG. 2, theDMA engine (195) and the DMA controller (195) support the messagingmodule (161).

For further explanation, FIG. 3A illustrates an exemplary Point To PointAdapter (180) useful in systems capable of optimizing JIT compiling fora Java application executing on a compute node according to embodimentsof the present invention. Point To Point Adapter (180) is designed foruse in a data communications network optimized for point to pointoperations, a network that organizes compute nodes in athree-dimensional torus or mesh. Point To Point Adapter (180) in theexample of FIG. 3A provides data communication along an x-axis throughfour unidirectional data communications links, to and from the next nodein the −x direction (182) and to and from the next node in the +xdirection (181). Point To Point Adapter (180) also provides datacommunication along a y-axis through four unidirectional datacommunications links, to and from the next node in the −y direction(184) and to and from the next node in the +y direction (183). Point ToPoint Adapter (180) in FIG. 3A also provides data communication along az-axis through four unidirectional data communications links, to andfrom the next node in the −z direction (186) and to and from the nextnode in the +z direction (185).

For further explanation, FIG. 3B illustrates an exemplary GlobalCombining Network Adapter (188) useful in systems capable of optimizingJIT compiling for a Java application executing on a compute nodeaccording to embodiments of the present invention. Global CombiningNetwork Adapter (188) is designed for use in a network optimized forcollective operations, a network that organizes compute nodes of aparallel computer in a binary tree. Global Combining Network Adapter(188) in the example of FIG. 3B provides data communication to and fromtwo children nodes through four unidirectional data communications links(190). Global Combining Network Adapter (188) also provides datacommunication to and from a parent node through two unidirectional datacommunications links (192).

For further explanation, FIG. 4 sets forth a line drawing illustratingan exemplary data communications network (108) optimized for point topoint operations useful in systems capable of optimizing JIT compilingfor a Java application executing on a compute node in accordance withembodiments of the present invention. In the example of FIG. 4, dotsrepresent compute nodes (102) of a parallel computer, and the dottedlines between the dots represent data communications links (103) betweencompute nodes. The data communications links are implemented with pointto point data communications adapters similar to the one illustrated forexample in FIG. 3A, with data communications links on three axes, x, y,and z, and to and fro in six directions +x (181), −x (182), +y (183), −y(184), +z (185), and −z (186). The links and compute nodes are organizedby this data communications network optimized for point to pointoperations into a three dimensional mesh (105). The mesh (105) haswrap-around links on each axis that connect the outermost compute nodesin the mesh (105) on opposite sides of the mesh (105). These wrap-aroundlinks form part of a torus (107). Each compute node in the torus has alocation in the torus that is uniquely specified by a set of x, y, zcoordinates. Readers will note that the wrap-around links in the y and zdirections have been omitted for clarity, but are configured in asimilar manner to the wrap-around link illustrated in the x direction.For clarity of explanation, the data communications network of FIG. 4 isillustrated with only 27 compute nodes, but readers will recognize thata data communications network optimized for point to point operationsfor use in optimizing JIT compiling for a Java application executing ona compute node in accordance with embodiments of the present inventionmay contain only a few compute nodes or may contain thousands of computenodes.

For further explanation, FIG. 5 sets forth a line drawing illustratingan exemplary data communications network (106) optimized for collectiveoperations useful in systems capable of optimizing JIT compiling for aJava application executing on a compute node in accordance withembodiments of the present invention. The example data communicationsnetwork of FIG. 5 includes data communications links connected to thecompute nodes so as to organize the compute nodes as a tree. In theexample of FIG. 5, dots represent compute nodes (102) of a parallelcomputer, and the dotted lines (103) between the dots represent datacommunications links between compute nodes. The data communicationslinks are implemented with global combining network adapters similar tothe one illustrated for example in FIG. 3B, with each node typicallyproviding data communications to and from two children nodes and datacommunications to and from a parent node, with some exceptions. Nodes ina binary tree (106) may be characterized as a physical root node (202),branch nodes (204), and leaf nodes (206). The root node (202) has twochildren but no parent. The leaf nodes (206) each has a parent, but leafnodes have no children. The branch nodes (204) each has both a parentand two children. The links and compute nodes are thereby organized bythis data communications network optimized for collective operationsinto a binary tree (106). For clarity of explanation, the datacommunications network of FIG. 5 is illustrated with only 31 computenodes, but readers will recognize that a data communications networkoptimized for collective operations for use in systems for optimizingJIT compiling for a Java application executing on a compute node inaccordance with embodiments of the present invention may contain only afew compute nodes or may contain thousands of compute nodes.

In the example of FIG. 5, each node in the tree is assigned a unitidentifier referred to as a ‘rank’ (250). A node's rank uniquelyidentifies the node's location in the tree network for use in both pointto point and collective operations in the tree network. The ranks inthis example are assigned as integers beginning with 0 assigned to theroot node (202), 1 assigned to the first node in the second layer of thetree, 2 assigned to the second node in the second layer of the tree, 3assigned to the first node in the third layer of the tree, 4 assigned tothe second node in the third layer of the tree, and so on. For ease ofillustration, only the ranks of the first three layers of the tree areshown here, but all compute nodes in the tree network are assigned aunique rank.

For further explanation, FIG. 6 sets forth a block diagram illustratingan exemplary system useful in optimizing JIT compiling for a Javaapplication executing on a compute node (600 a) according to embodimentsof the present invention. The compute node (600 a) is included in aparallel computer along with other compute nodes (600 b). Each computenode (600) has installed upon it a JVM (200) capable of supporting aJava application (158).

The nodes (600) of FIG. 6 are connected together for data communicationsusing a data communication network. In addition, the nodes (600) areconnected to an I/O node (110) that provides I/O services between thenodes (600) and a set of I/O devices such as, for example, the servicenode (116) and the data storage (118). The service node (116) of FIG. 6provides services common to nodes (600), administering the configurationof nodes (600), loading programs such as Java application (158) and JVM(200) onto the nodes (600), starting program execution on the nodes(600), retrieving results of program operations on the nodes (600), andso on. The data storage (118) of FIG. 6 may store the files that containthe Java classes that compose the Java application (158).

The service node (116) has installed upon it an application manager(125). The application manager (125) includes a set of computer programinstructions capable of optimizing JIT compiling for a Java applicationexecuting on a compute node according to embodiments of the presentinvention. The application manager (125) operates generally foroptimizing JIT compiling for a Java application executing on a computenode according to embodiments of the present invention by: identifyingparticular portion of the Java application (158) and assigning a JITlevel to the particular portion of the Java application (158). In such amanner, optimizing JIT compiling for a Java application executing on acompute node according to embodiments of the present inventionadvantageously allows for different portions of a single application tobe compiled and optimized using different JIT levels.

The level of granularity at which JIT levels are assigned to anapplication may vary depending on the implementation of the particularapplication portions to which the JIT levels are assigned. Theparticular portion of the Java application (158) may be implemented as ageneric type of Java construct, a specific implementation of a Javaconstruct, a call sequence for a particular Java method, and so on. Ageneric type of Java construct is a Java specific programming structuresuch as, for example, a class, a packet, a method, a Java Archive, andso on. A specific implementation of a Java construct is an actualinstance of a generic type of Java construct. For example, foo( ) is anexample of a specific implementation of a Java method. A call sequencefor a particular Java method is the set of instructions in the executionpath for a particular Java method from the method's beginning to themethod's end. That is, call sequence for a particular Java methodincludes all of the computer program instructions in that particularmethod and any instructions of the methods invoked by that particularmethod.

Using these different exemplary application portions, the applicationmanager (125) of FIG. 6 may assign a different JIT level to any one ofthese generic types of Java constructs, specific implementations of Javaconstructs, or call sequences for a particular Java method. For furtherexplanation, consider that the application includes a Java Archive(‘JAR’) file that, in turn, includes a variety of Java classes. Considerthat one of these Java classes is called ‘foo_class,’ and foo_classincludes a method called ‘foo_method,’ which in turn calls a methodnamed ‘foo2_method.’ Further consider that the JIT levels available to aparticular JVM are ‘low,’ ‘medium,’ ‘high,’ and ‘ultra high.’ In such anexample, the application manager (125) may assign a JIT level of low tothe entire exemplary Java Archive, a JIT level of medium to foo_class, aJIT level of high to foo_method, and a JIT level of ultra high tofoo2_method. In such a manner, different portion of the application hasassigned different JIT levels.

In the example of FIG. 6, the application manager (125) assigns JITlevels to the various portions of application (158) in a JIT profile(652). The JIT profile (652) of FIG. 6 is a data structure used by theJVM (200) that associates a JIT level with a portion of the application(158). The JIT profile (652) may be formatted as a text file, a table, astructured document, or any other format as will occur to those of skillin the art. The application manager (125) may assign JIT levels to thevarious portions of application (158) in a JIT profile (652) based onuser-specified JIT levels for the various portions of the application(158) or based on a historic execution performance for the variousportions of the application (158).

The JVM (200) of FIG. 6 includes a storage area for just-in time (‘JIT’)code (616), equivalent to method byte code which has already beencompiled into machine code to be run directly on the native platform.This code is created by the JVM (200) from Java byte code by acompilation and optimization process using JIT compiler (618), typicallywhen the application program is started up or when some other usagecriterion is met, and is used to improve run-time performance byavoiding the need for this code to be interpreted later.

The JIT compiler (618) of FIG. 6 operates generally for optimizing JITcompiling for a Java application executing on a compute node accordingto embodiments of the present invention by jitting each particularportion of the Java application (158) in dependence upon the JIT levelassigned to that particular portion of the Java application. The JITcompiler (618) spawns a compilation thread that receives the byte-codeversion of the application (158), translates and optimizes the byte codeinto native code, and feeds the native code to an execution thread forthe JIT code executor (654). After processing various portions of theapplication (158), the JIT compiler (618) examines the portions of theapplication (158) executed by the JIT code executor (654). The JITcompiler (618) may update the JIT profile (652) for the application(158) based on how the JIT code executor (654) executed the application(158). For example, if portions of the application are consistentlybeing skipped during execution, the JIT compiler (618) may specify a JITlevel in the JIT profile (652) for those skipped portions that instructsthe JIT compiler (618) to skip compilation and optimization for thoseskipped portions. Similarly, if portions of the application are beingexecuted repeatedly, the JIT compiler (618) may specify a JIT level inthe JIT profile (652) for those repeatedly used portions that instructthe JIT compiler (618) to compile and fully optimization for thoserepeatedly used portions.

The Java application (158) included on the compute node (600 a) iscomposed of any number of Java classes. In addition, the node (600 a) ofFIG. 6 includes a JVM (200) to provide a virtual execution environmentfor executing the Java application (158). As the JVM (200) executes theJava application (158), the JVM identifies a Java class utilized for theJava application (158). After the Java class is identified, the JVM(200) loads the Java classes for the application (158) into memory andprepare each class instance for execution. The JVM (200) thereforeincludes a hierarchy of class loaders (620) that operate to load theclasses specified by the application (158). The hierarchy of classloaders (620) includes a primordial class loader (622), an extensionclass loader (624), and an application class loader (626).

The primordial class loader (622) of FIG. 6 loads the core Javalibraries, such as ‘core.jar,’ ‘server.jar,’ and so on, in the‘<JAVA_HOME>/lib’ directory. The primordial class loader (622), which ispart of the core JVM, is written in native code specific to the hardwareplatform on which the JVM is installed. The extension class loader (624)of FIG. 6 loads the code in the extensions directories and is typicallyimplemented by the ‘sun.misc.Launcher$ExtClassLoader’ class. Theapplication class loader (626) of FIG. 6 loads the class specified by‘java.class.path,’ which maps to the system ‘CLASSPATH’ variable. Theapplication class loader (626) is typically implemented by the‘sun.misc.Launcher$AppClassLoader’ class.

For each class included or specified by the Java application (158), theJVM (200) effectively traverses up the class loader hierarchy todetermine whether any class loader has previously loaded the class. Theorder of traversal is as follows: first to the default application classloader (626), then to the extension class loader (624), and finally tothe primordial class loader (622). If the response from all of the classloaders is negative, then the JVM (200) traverses down the hierarchy,with the primordial class loader first attempting to locate the class bysearching the locations specified in its class path definition. If theprimordial class loader (622) is unsuccessful, then the then theextension class loader (624) may make a similar attempt to load theclass. If the extension class loader (624) is unsuccessful, then theapplication class loader (626) attempts to load the class. Finally, ifthe application class loader (626) is unsuccessful, then the JVM (200)triggers an error condition.

The JVM (200) of FIG. 6 also includes a heap (610), which is sharedbetween all threads, and is used for storage of objects (612). Eachobject (612) represents an already loaded class. That is, each object(612) is in effect an instantiation of a class, which defines theobject. Because an application (158) may utilize more than one object ofthe same type, a single class may be instantiated multiple times tocreate the objects specified by the application (158). Readers will notethat the class loaders (620) are objects that are also stored on heap(610), but for the sake of clarity the class loaders (620) are shownseparately in FIG. 6.

In the example of FIG. 6, the JVM (200) also includes a class storagearea (636), which is used for storing information relating to theclasses stored in the heap (610). The class storage area (636) includesa method code region (638) for storing byte code for implementing classmethod calls, and a constant pool (640) for storing strings and otherconstants associated with a class. The class storage area (636) alsoincludes a field data region (642) for sharing static variables, whichare shared between all instances of a class, and a static initializationarea (646) for storing static initialization methods and otherspecialized methods separate from the method code region (638). Theclass storage area also includes a method block area (644), which isused to stored information relating to the code, such as invokers, and apointer to the code, which may for example be in method code area (638),in JIT code area (616) described in detail below, or loaded as nativecode such as, for example, a dynamic link library (‘DLL’) written in Cor C++.

A class stored as an object (612) in the heap (610) contains a referenceto its associated data, such as method byte code, in class storage area(636). Each object (612) contains a reference to the class loader (620),which loaded the class into the heap (610), plus other fields such as aflag to indicate whether or not they have been initialized.

In the example of FIG. 6, the JVM (200) also includes a stack area(614), which is used for storing the stacks associated with theexecution of different threads on the JVM (200). Readers will note thatbecause the system libraries and indeed parts of the JVM (200) itselfare written in Java, which frequently utilize multi-threading, the JVM(200) may be supporting multiple threads even if the Java application(158) contains only a single thread.

Also included within JVM (200) of FIG. 6 is a class loader cache (634)and garbage collector (650). The former is typically implemented as atable that allows a class loader to trace those classes which itinitially loaded into the JVM (200). The class loader cache (634)therefore allows each class loader (620) to determine whether it hasalready loaded a particular class when the JVM (200) initially traversesthe class loader hierarchy as described above. Readers will note that itis part of the overall security policy of the JVM (200) that classeswill typically have different levels of permission within the systembased on the identity of the class loader by which they were originallyloaded.

The garbage collector (650) is used to delete objects (612) from heap(610) when they are no longer required. Thus in the Java programminglanguage, applications do not need to specifically request or releasememory, rather this is controlled by the JVM (200) itself. Therefore,when the Java application (158) specifies the creation of an object(612), the JVM (200) secures the requisite memory resource. Then, whenthe Java application finishes using object (612), the JVM (200) candelete the object (612) to free up this memory resource. This process ofdeleting an object is known as ‘garbage collection,’ and is generallyperformed by briefly interrupting all threads on the stack (614), andscanning the heap (610) for objects (612) which are no longerreferenced, and therefore can be deleted. The details of garbagecollection vary from one JVM (200) implementation to another, buttypically garbage collection is scheduled when the heap (610) is nearlyexhausted and so there is a need to free up space for new objects (612).

In the example of FIG. 6, the JVM (200) also includes a monitor pool(648). The monitor pool (648) is used to store a set of locks or‘monitors’ that are used to control contention to an object resultingfrom concurrent attempts to access the object by different threads whenexclusive access to the object is required.

Although the JVM (200) in FIG. 6 is shown on and described above withregard to the node (600 a), readers will note that each of the othernodes (600 b) also has installed upon it a JVM configured in a similarmanner. That is, each of the other nodes (600 b) also has installed uponit a JVM capable of optimizing JIT compiling for a Java applicationaccording to embodiments of the present invention.

FIG. 7 sets forth a flow chart illustrating an exemplary method foroptimizing JIT compiling for a Java application executing on a computenode according to embodiments of the present invention. The compute nodedescribed with reference to FIG. 7 has installed upon it a JVM capableof supporting the Java application (158). For discussion purposes forthe remainder of the description with reference to FIG. 7, consider thefollowing pseudo code representing an exemplary Java application:

01: ... 02: public class FooClass { 03: static void foo2(...) { 04: ...05: return; 06: } 07: static void foo(...) { 08: ... 09:FooClass.foo2(...); 10: ... 11: return; 12: ... 13: public static voidmain (String[ ] args) { 14: ... 15: while (test) { 16:FooClass.foo(...); 17: } 18: ... 19:SomeOtherClass.someOtherMethod(...); 20: ... 21: } 22: } 23: ...

The pseudo code above references three Java classes ‘FooClass,’ ‘main,’and ‘SomeOtherClass.’ The main class invokes a member method of FooClasscalled ‘foo’ within a loop and a member method of SomeOtherClass called‘someOtherMethod.’ In turn, the foo method invokes another member methodof the FooClass called ‘foo2.’ Readers will note that the exemplary Javaapplication represented by the pseudo code above is for explanation onlyand not for limitation.

The method of FIG. 7 includes identifying (700), by an applicationmanager, particular portion (702) of the Java application (158). Theapplication manager may be installed on the same compute node as theJava application (158) or the application manager may be installed onsome other computer that accesses the Java application (158) through adata communications connection. The application manager may identify(700) the particular portion (702) of the Java application (158)according to the method of FIG. 7 by determining a specific applicationportion (702) to be identified and parsing the byte code representingthe application (158) for the specific application portion to beidentified. The specific application portion to be identified may bespecified by a system administrator responsible for application JITperformance, or the specific application portion may be somepreconfigured application portion. As mentioned above, the particularportions to be identified may include generic types of Java constructs,specific implementations of Java constructs, call sequences forparticular Java methods, and so on. Accordingly, a system administratormay instruct the application manager to identify a particular genericJava construct type, specific implementation of a Java construct, or aspecific call sequence for a particular Java method for assigning a JITlevel.

For further explanation of identifying (700) a particular portion (702)of the Java application (158), consider again the exemplary pseudo codeabove representing an exemplary application. When the specific portionto be identified is a generic type of Java construct such as, forexample, a Java class, the application manager may identify thefollowing portions of the exemplary Java application:

TABLE 1 EXEMPLARY PORTIONS OF A JAVA APPLICATION PORTION IDENTIFIERPORTION POSITION Main Lines 13-21 FooClass Lines 2-22

The exemplary table 1 above illustrates two Java classes identified bythe application manager. The first portion is the Java class ‘main’positioned at lines 13-21. The second portion is the Java class‘FooClass’ positioned at lines 2-22. The positions are represented aslines number in the example above, but readers will note that theposition may be represented in any number of ways as will occur to thoseof skill in the art including line numbers, memory locations, programcounters, and so on. Readers will also note that exemplary applicationportions illustrated in table 1 are for explanation only and not forlimitation.

For an additional example of identifying (700) a particular portion(702) of the Java application (158), consider again the exemplary pseudocode above representing an exemplary application. When the specificportion to be identified is a specific implementation of a Javaconstruct such as, for example, the method ‘foo,’ the applicationmanager may identify the following portions of the exemplary Javaapplication:

TABLE 2 EXEMPLARY PORTIONS OF A JAVA APPLICATION PORTION IDENTIFIERPORTION POSITION foo Lines 7-11

The exemplary table 2 above describes that the method ‘foo’ ispositioned at lines 7-11 in the exemplary pseudo code above. Again,readers will note that exemplary application portions illustrated intable 2 are for explanation only and not for limitation.

For another example of identifying (700) a particular portion (702) ofthe Java application (158), consider again the exemplary pseudo codeabove representing an exemplary application. When the specific portionto be identified is a specific implementation of a Java construct suchas, for example, the call sequence for the method ‘foo,’ the applicationmanager may identify the following portions of the exemplary Javaapplication:

TABLE 3 EXEMPLARY PORTIONS OF A JAVA APPLICATION PORTION IDENTIFIERPORTION POSITION foo Lines 7-11 and Lines 3-6

The exemplary table 3 above describes that the call sequence for themethod ‘foo’ includes computer program instructions positioned at lines7-11 and lines 3-6 in the exemplary pseudo code above. Again, readerswill note that exemplary application portions illustrated in table 3 arefor explanation only and not for limitation.

The method of FIG. 7 includes assigning (704), by the applicationmanager, a JIT level (710) to the particular portion (702) of the Javaapplication (158). In the method of FIG. 7, the application managerassigns (704) a JIT level (710) to the particular portion (702) of theJava application (158) by establishing (706) the JIT level (710) for theparticular portion (702) of the Java application (158) in dependenceupon a historic JIT profile (708) for the particular portion (702) ofthe Java application (158). The historic JIT profile (708) of FIG. 7represents a data structure used by the JVM that specifies JIT levelspreviously used when jitting various portions of the application (158).The previous execution performance (709) of FIG. 7 represents a datastructure used by the JVM that specifies historic execution performancefor the various portions of the application (158). Using the historicJIT profile (708) and the previous execution performance (709), theapplication manager may establish (706) the JIT level (710) for theparticular portion (702) of the Java application (158) according to themethod of FIG. 7 by determining whether a previous performance value forthe particular portion (702) is below a performance threshold andwhether the number of times the portion was invoked exceeds a repetitionthreshold, and incrementing the JIT level if the pervious performancevalue is below the performance threshold and the number of times theportion was invoked exceeds a repetition threshold.

For further explanation of assigning (704) a JIT level (710) to theparticular portion (702) of the Java application (158), consider againthe exemplary pseudo code above representing an exemplary application.Also consider that the previous execution performance for the variousportions of the application is normalized on a scale of 1 to 10-1 beingthe lowest performance and 10 being the highest performance—and are asfollows for the various portions of the application:

TABLE 4 EXEMPLARY PREVIOUS EXECUTION PERFORMANCE PERFORMANCE INVOCATIONPORTION IDENTIFIER VALUE VALUE FooClass 2 1000 foo2 3 1000 foo 1 1000main 4 1 SomeOtherClass 9 1 someOtherMethod 10 1 while construct 1 1000Java Classes 5 1001 Java Methods 4 2001 Call Sequence foo 1 1000

Table 4 above describes the previous execution performance of variousportions of the exemplary application. The Java class FooClass exhibitedrelatively poor performance with a value of 2 and was invoked 1000times. The Java method foo2 exhibited slightly better performance thanthe overall FooClass with a performance value of 3 and was invoked 1000times. The Java method foo exhibited poor performance with a value of 1and was also invoked 1000 times. The Java class main exhibitedperformance of 4 and was invoked only once. The Java classSomeOtherClass exhibited relatively high performance with a value of 9and was invoked only once, and the Java method someOtherMethod alsoexhibited relatively high performance with a value of 10 and was invokedonly once. The Java construct implemented as a while loop had relativelypoor performance with a value of 1 and was invoked 1000 times. Overall,the Java Classes in the application had a performance value of 5 andwere invoked 1001 times, and the Java methods overall had a performancevalue of 4 and were invoked 2001 times. The call sequence for the foomethod, however, had a poor performance value of 1 and was invoked 1000times. Readers will note that the table above is for example andexplanation only and not for limitation.

Now consider an exemplary historical JIT profile for each of theportions in Table 4 where the JIT levels are low, medium, high, andultra high for the various portions of the application:

TABLE 5 EXEMPLARY HISTORIC JIT PROFILE PORTION IDENTIFIER JIT LEVELFooClass Low foo2 Low foo Low main Medium SomeOtherClass Ultra HighsomeOtherMethod Ultra High while construct Low Java Classes Medium JavaMethods Medium Call Sequence foo Low

Using the exemplary tables 4 and 5 above, the application manager mayassign JIT levels to each of the portions of the exemplary applicationsuch that JIT level is increased for the application portions with poorprevious execution performance but often invoked such as, for example,FooClass, foo2, foo, the while construct, and the call sequence for foo.The following table illustrates exemplary JIT level assigned by anapplication manager based on the exemplary historic JIT profile in table4 and the exemplary previous execution performance of Table 5:

TABLE 6 EXEMPLARY JIT LEVELS PORTION IDENTIFIER JIT LEVEL FooClass UltraHigh foo2 Ultra High foo Ultra High main Medium SomeOtherClass UltraHigh someOtherMethod Ultra High while construct Ultra High Java ClassesMedium Java Methods Medium Call Sequence foo Ultra High

From Table 6 above, readers will note that the JIT levels for exemplaryapplication portions FooClass, foo2, foo, the while construct, and thecall sequence for foo have all been increased from ‘low’ to ‘ultra high’because their previous execution performance was poor and these portionsof the application were often invoked. Again, readers will note that theexamples above are for explanation only and not for limitation.

Although assigning (704) a JIT level (710) to the particular portion(702) is described above based on historic JIT profile (708), readerswill note that in some other embodiments, the application manager mayassign (704) a JIT level (710) to the particular portion (702) of theJava application (158) based on predictive application performance forthe various portions of the application (158). Still further, in someother embodiments, the application manager may assign (704) a JIT level(710) to the particular portion (702) of the Java application (158)based on predefined JIT levels for the various portions of theapplication (158) provided by a system administrator or an applicationdeveloper.

The method of FIG. 7 also includes jitting (712), by the JVM installedon the compute node, the particular portion (702) of the Javaapplication (158) in dependence upon the JIT level (710) assigned tothat particular portion (702) of the Java application (158). The JVM mayjit (712) the particular portion (702) of the Java application (158) independence upon the JIT level (710) assigned to that particular portion(702) according to the method of FIG. 7 by setting the JVM jit mode tothe JIT level assigned to the particular portion (702) upon encounteringthat particular portion (702) of the application (158), translating andoptimizing the byte code representations of that portion (702) into JITcode (616), and providing the JIT code (616) to the JVM's executionthread for execution on the processor of the compute node. Readers willnote that the level of optimization performed on the various portions ofthe application (158) vary according to the JIT level assigned to thoseportions. In such a manner, usage of the JVM's jitting resources canenhanced because portions of the application that do not benefit fromhigh levels of optimization can be assigned low JIT levels and otherportions that will benefit from optimization can be assigned high JITlevels. Moreover, optimizing JIT compiling for a Java applicationexecuting on a compute node according to embodiments of the presentinvention allows a system administrator or application developer havingknowledge of other relevant computing factors to assign low JIT levelsto portions of applications where initialization and startup time shouldbe minimized despite the fact that those portions will benefit fromhigher levels of optimization associated with higher JIT levels.

Exemplary embodiments of the present invention are described largely inthe context of a fully functional computer system for optimizing JITcompiling for a Java application executing on a compute node. Readers ofskill in the art will recognize, however, that the present inventionalso may be embodied in a computer program product disposed on computerreadable media for use with any suitable data processing system. Suchcomputer readable media may be transmission media or recordable mediafor machine-readable information, including magnetic media, opticalmedia, or other suitable media. Examples of recordable media includemagnetic disks in hard drives or diskettes, compact disks for opticaldrives, magnetic tape, and others as will occur to those of skill in theart. Examples of transmission media include telephone networks for voicecommunications and digital data communications networks such as, forexample, Ethernets™ and networks that communicate with the InternetProtocol and the World Wide Web as well as wireless transmission mediasuch as, for example, networks implemented according to the IEEE 802.11family of specifications. Persons skilled in the art will immediatelyrecognize that any computer system having suitable programming meanswill be capable of executing the steps of the method of the invention asembodied in a program product. Persons skilled in the art will recognizeimmediately that, although some of the exemplary embodiments describedin this specification are oriented to software installed and executingon computer hardware, nevertheless, alternative embodiments implementedas firmware or as hardware are well within the scope of the presentinvention.

It will be understood from the foregoing description that modificationsand changes may be made in various embodiments of the present inventionwithout departing from its true spirit. The descriptions in thisspecification are for purposes of illustration only and are not to beconstrued in a limiting sense. The scope of the present invention islimited only by the language of the following claims.

What is claimed is:
 1. A method of optimizing just-in-time (‘JIT’)compiling for a software application executing on a compute node, thecompute node having installed upon it a software Virtual Machine (‘VM’)capable of supporting the software application, the method comprising:identifying, by an application manager, a particular portion of thesoftware application; assigning, by the application manager, a JIT levelto the particular portion of the software application, including:establishing the JIT level for the particular portion of the softwareapplication in dependence upon a historic JIT profile for the particularportion of the software application and previous execution performanceof the particular portion of the software application, wherein theprevious execution performance for the particular portion includes aprevious performance value and a number of times the particular portionwas invoked, wherein the historic JIT profile specifies JIT levelspreviously used when jitting various portions of the softwareapplication; and jitting, by the VM installed on the compute node, theparticular portion of the software application in dependence upon theJIT level assigned to that particular portion of the softwareapplication.
 2. The method of claim 1 wherein the particular portion ofthe software application further comprises a generic type of softwareconstruct.
 3. The method of claim 1 wherein the particular portion ofthe software application further comprises a specific implementation ofa software construct.
 4. The method of claim 1 wherein the particularportion of the software application further comprises a software callsequence for a particular software method.
 5. (canceled)
 6. The methodof claim 1 wherein optimizing JIT compiling for a software applicationexecuting on a compute node further comprises optimizing JIT compilingfor a software application executing on a parallel computer, theparallel computer comprising a plurality of compute nodes and a servicenode, the application manager installed upon the service node, theplurality of compute nodes connected for data communications through aplurality of data communications networks, at least one datacommunications network optimized for collective operations, and at leastone other data communications network optimized for point to pointoperations.
 7. A compute node capable of optimizing just-in-time (‘JIT’)compiling for a software application, the compute node having installedupon it a software Virtual Machine (‘VM’) capable of supporting thesoftware application, the compute node comprising a computer processorand computer memory operatively coupled to the computer processor, thecomputer memory for the compute node having disposed within it computerprogram instructions capable of: identifying a particular portion of thesoftware application; assigning, by the application manager, a JIT levelto the particular portion of the software application, including:establishing the JIT level for the particular portion of the softwareapplication in dependence upon a historic JIT profile for the particularportion of the software application and previous execution performanceof the particular portion of the software application, wherein theprevious execution performance for the particular portion includes aprevious performance value and a number of times the particular portionwas invoked, wherein the historic JIT profile specifies JIT levelspreviously used when jitting various portions of the softwareapplication; and jitting, by the VM installed on the compute node, theparticular portion of the software application in dependence upon theJIT level assigned to that particular portion of the softwareapplication.
 8. The compute node of claim 7 wherein the particularportion of the software application further comprises a generic type ofsoftware construct.
 9. The compute node of claim 7 wherein theparticular portion of the software application further comprises aspecific implementation of a software construct.
 10. The compute node ofclaim 7 wherein the particular portion of the software applicationfurther comprises a software call sequence for a particular softwaremethod.
 11. (canceled)
 12. The compute node of claim 7 whereinoptimizing JIT compiling for a software application executing on acompute node further comprises optimizing JIT compiling for a softwareapplication executing on a parallel computer, the parallel computercomprising a plurality of compute nodes and a service node, theapplication manager installed upon the service node, the plurality ofcompute nodes connected for data communications through a plurality ofdata communications networks, at least one data communications networkoptimized for collective operations, and at least one other datacommunications network optimized for point to point operations.
 13. Acomputer program product for optimizing just-in-time (‘JIT’) compilingfor a software application executing on a compute node, the compute nodehaving installed upon it a software Virtual Machine (‘VM’) capable ofsupporting the software application, the computer program productdisposed upon a computer readable medium, the computer program productcomprising computer program instructions capable of: identifying, by anapplication manager, a particular portion of the software application;assigning, by the application manager, a JIT level to the particularportion of the software application, including: establishing the JITlevel for the particular portion of the software application independence upon a historic JIT profile for the particular portion of thesoftware application and previous execution performance of theparticular portion of the software application, wherein the previousexecution performance for the particular portion includes a previousperformance value and a number of times the particular portion wasinvoked, wherein the historic JIT profile specifies JIT levelspreviously used when jitting various portions of the softwareapplication; and jitting, by the VM installed on the compute node, theparticular portion of the software application in dependence upon theJIT level assigned to that particular portion of the softwareapplication.
 14. The computer program product of claim 13 wherein theparticular portion of the software application further comprises ageneric type of software construct.
 15. The computer program product ofclaim 13 wherein the particular portion of the software applicationfurther comprises a specific implementation of a software construct. 16.The computer program product of claim 13 wherein the particular portionof the software application further comprises a software call sequencefor a particular software method.
 17. (canceled)
 18. The computerprogram product of claim 13 wherein optimizing JIT compiling for asoftware application executing on a compute node further comprisesoptimizing JIT compiling for a software application executing on aparallel computer, the parallel computer comprising a plurality ofcompute nodes and a service node, the application manager installed uponthe service node, the plurality of compute nodes connected for datacommunications through a plurality of data communications networks, atleast one data communications network optimized for collectiveoperations, and at least one other data communications network optimizedfor point to point operations.
 19. The computer program product of claim13 wherein the computer readable medium comprises a recordable medium.20. The computer program product of claim 13 wherein the computerreadable medium comprises a transmission medium.